{"id":58424,"date":"2020-08-07T19:17:11","date_gmt":"2020-08-07T10:17:11","guid":{"rendered":"https:\/\/smilegate.ai\/?p=58424"},"modified":"2020-08-16T22:35:02","modified_gmt":"2020-08-16T13:35:02","slug":"google-mixit-ai","status":"publish","type":"post","link":"https:\/\/smilegate.ai\/en\/2020\/08\/07\/google-mixit-ai\/","title":{"rendered":"Google MixIT AI-Separation of unsupervised learning sound sources"},"content":{"rendered":"

MixIT AI, unveiled by Google, is a technology that obtains a separate sound source from single channel audio in which multiple sound sources are mixed. It can be viewed as a blind source separation task, and unlike existing technologies, it is characterized by excellent performance with unsupervised(!).<\/p>\n\n\n\n

The recent trend is clear. Unsupervised, self-supervised, semi-supervised, the names are slightly different, but in the end what you want is to catch up with performance by using unlabeled data on a large scale, rather than having a medium-sized labeled data. And adding more data there or achieving SOTA with very little labeling data.<\/p>\n\n\n\n

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